Screening of key risk SNPs for glioma based on machine learning algorithms

Glioma is a common primary malignant brain tumor and is the most aggressive and lethal solid tumor, accounting for approximately 80% of all intracranial malignancies. Our aim was to screen key SNP by LASSO regression and random forest (a machine learning algorithm) and construct a model based on these SNP to predict the risk of glioma in Chinese Han population.